Pezzutto, Matthias, Tramarin, Federico, Dey, Subhrakanti and Schenato, Luca (2020) Adaptive transmission rate for LQG control over Wi-Fi: A cross-layer approach. Automatica, 119. p. 109092. ISSN 00051098
Preview
1-s2.0-S0005109820302909-main.pdf
Download (1MB) | Preview
Abstract
This work studies the problem of LQG control when the link between the sensor and the controller relies on a Wi-Fi network. Unfortunately, the communication on a wireless medium is sensitive to noise in the transmission band, which is characterized by the Signal-to-Noise Ratio (SNR). Wi-Fi allows to switch among different bit-rates in real-time thus permitting to trade-off lower loss probabilities for larger latency or vice-versa to achieve better closed-loop performance. To exploit this feature, under a constant SNR scenario, we propose a cross-layer approach where the bit-rate is optimally selected based on a control performance metric (i.e. minimum LQG cost) and a model-based controller is used to compensate for the packet losses. Under time-varying SNR, we additionally propose a (sub-optimal) on-line rate adaptation strategy and we guarantee the closed-loop stability under some mild conditions. Numerical comparisons with emulation-based approaches using TrueTime, a realistic Matlab-based Wi-Fi simulator, are included to show the benefits of the adaptive approach under time-varying SNR scenarios.
Item Type: | Article |
---|---|
Keywords: | Wi-Fi; Rate selection; LQG; Control over wireless; Packet loss; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 16355 |
Identification Number: | 10.1016/j.automatica.2020.109092 |
Depositing User: | Subhrakanti Dey |
Date Deposited: | 27 Jul 2022 07:55 |
Journal or Publication Title: | Automatica |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/16355 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
Downloads
Downloads per month over past year